國立高雄大學圖資館 |

Language: English

Back

Advanced analytics and learning on t...

(1998 :)

Advanced analytics and learning on temporal data6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021 : revised selected papers /

Record Type:	Electronic resources : Monographic component part
Title/Author:	Advanced analytics and learning on temporal dataedited by Vincent Lemaire ... [et al.].
Reminder of title:	6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021 : revised selected papers /
remainder title:	AALTD 2021
other author:	Lemaire, Vincent.
corporate name:
Published:	Cham :Springer International Publishing :2021.
Description:	x, 195 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Data Mining and Knowledge Discovery.
Online resource:	https://doi.org/10.1007/978-3-030-91445-5
ISBN:	9783030914455$q(electronic bk.)

Advanced analytics and learning on temporal data6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021 : revised selected papers /
Advanced analytics and learning on temporal data6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021 : revised selected papers /[electronic resource] :AALTD 2021edited by Vincent Lemaire ... [et al.]. - Cham :Springer International Publishing :2021. - x, 195 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,131140302-9743 ;. - Lecture notes in computer science ;4891..

Oral Presentation -- Ranking by Aggregating Referees: Evaluating the Informativeness of Explanation Methods for Time Series Classification -- State Space approximation of Gaussian Processes for time-series forecasting -- Fast Channel Selection for Scalable Multivariate Time Series Classification -- Temporal phenotyping for characterisation of hospital care pathways of COVID patients -- A New Multivariate Time Series Co-clustering Non-Parametric Model Applied to Driving-Assistance Systems Validation -- TRAMESINO: Trainable Memory System for Intelligent Optimization of Road Traffic Control -- Detection of critical events in renewable energy production time series -- Poster Presentation -- Multimodal Meta-Learning for Time Series Regression -- Cluster-based Forecasting for Intermittent and Non-intermittent Time Series -- State discovery and prediction from multivariate sensor data -- RevDet: Robust and Memory Efficient Event Detection and Tracking in Large News Feeds -- From Univariate to Multivariate Time Series Anomaly Detection with Non-Local Information.

This book constitutes the refereed proceedings of the 6th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2021, held during September 13-17, 2021. The workshop was planned to take place in Bilbao, Spain, but was held virtually due to the COVID-19 pandemic. The 12 full papers presented in this book were carefully reviewed and selected from 21 submissions. They focus on the following topics: Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Multivariate Time Series Co-clustering; Efficient Event Detection; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Cluster-based Forecasting; Explanation Methods for Time Series Classification; Multimodal Meta-Learning for Time Series Regression; and Multivariate Time Series Anomaly Detection.

ISBN: 9783030914455$q(electronic bk.)

Standard No.: 10.1007/978-3-030-91445-5doiSubjects--Topical Terms:

275288
Data Mining and Knowledge Discovery.

LC Class. No.: Q325.5 / .A35 2021

Dewey Class. No.: 006.31

Advanced analytics and learning on temporal data6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021 : revised selected papers /
LDR:03134nmam 220036175a 450 001 613918
003 DE-He213
005 20211129224946.0
006 m d
007 cr nn 008maaau
008 220627s2021 sz s 0 eng d
020 $a 9783030914455$q(electronic bk.)
020 $a 9783030914448$q(paper)
024 7 $a 10.1007/978-3-030-91445-5 $2 doi
035 $a 978-3-030-91445-5
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5 $b .A35 2021
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .A244 2021
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Advanced analytics and learning on temporal data $h [electronic resource] : $b 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021 : revised selected papers / $c edited by Vincent Lemaire ... [et al.].
246 3 $a AALTD 2021
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a x, 195 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 13114
490 1 $a Artificial intelligence
505 0 $a Oral Presentation -- Ranking by Aggregating Referees: Evaluating the Informativeness of Explanation Methods for Time Series Classification -- State Space approximation of Gaussian Processes for time-series forecasting -- Fast Channel Selection for Scalable Multivariate Time Series Classification -- Temporal phenotyping for characterisation of hospital care pathways of COVID patients -- A New Multivariate Time Series Co-clustering Non-Parametric Model Applied to Driving-Assistance Systems Validation -- TRAMESINO: Trainable Memory System for Intelligent Optimization of Road Traffic Control -- Detection of critical events in renewable energy production time series -- Poster Presentation -- Multimodal Meta-Learning for Time Series Regression -- Cluster-based Forecasting for Intermittent and Non-intermittent Time Series -- State discovery and prediction from multivariate sensor data -- RevDet: Robust and Memory Efficient Event Detection and Tracking in Large News Feeds -- From Univariate to Multivariate Time Series Anomaly Detection with Non-Local Information.
520 $a This book constitutes the refereed proceedings of the 6th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2021, held during September 13-17, 2021. The workshop was planned to take place in Bilbao, Spain, but was held virtually due to the COVID-19 pandemic. The 12 full papers presented in this book were carefully reviewed and selected from 21 submissions. They focus on the following topics: Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Multivariate Time Series Co-clustering; Efficient Event Detection; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Cluster-based Forecasting; Explanation Methods for Time Series Classification; Multimodal Meta-Learning for Time Series Regression; and Multivariate Time Series Anomaly Detection.
650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Computer Communication Networks. $3 218087
650 2 4 $a Computer Appl. in Social and Behavioral Sciences. $3 274376
650 2 4 $a Computers and Education. $3 274532
650 0 $a Machine learning $v Congresses. $3 384498
650 0 $a Control theory $v Congresses. $3 387290
650 1 4 $a Artificial Intelligence. $3 212515
700 1 $a Lemaire, Vincent. $3 860732
710 2 $a SpringerLink (Online service) $3 273601
711 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 4891. $3 383229
830 0 $a Artificial intelligence. $3 910708
856 4 0 $u https://doi.org/10.1007/978-3-030-91445-5
950 $a Computer Science (SpringerNature-11645)